MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header Authorization: Bearer <token> for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "" } after the user pastes, or with no args to get the link.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint=true and destructiveHint=false. Description adds context about the two authentication methods, the behavior of calling with or without token, and the permanence of config-based auth. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single paragraph with clear, actionable sentences. No unnecessary words. Could be slightly more structured (e.g., bullet points), but remains concise and front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple authentication tool with one optional parameter, the description covers the essential workflow: two login methods, token format, and best practice. No output schema, but the behavior is adequately described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has one optional parameter 'token' with no description. Description explains that token is a JWT and clarifies the two scenarios: pass token for session login or omit to get a link. This adds necessary meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'authenticate' and the resource 'MCP.AI for IDE agents'. Distinguishes from siblings by being the only authentication tool among many feegow and other tools. Explains two methods of login: permanent via config header or session via token.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use the tool (for login) and provides context for two use cases. Does not explicitly mention when not to use, but the purpose is clear and well-scoped.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have identical descriptions (e.g., multiple tools with same 'Read appointments and scheduling data' text) and only differ by a 'flattened action' label, making it impossible for an agent to distinguish which tool to call for a specific operation.
Names follow a loose verb_noun pattern but are extremely inconsistent: some use underscores, some have redundant prefixes like 'feegow_appointment_', and the same actions are duplicated across multiple tool names (e.g., 'list' appears in many). The 'flattened action' suffix is confusing.
94 tools is far too many for a clinic management system. This is clearly due to a one-action-per-tool design that fragments the API surface, making the server bloated and hard to navigate. A typical well-structured server for this domain would have 10-20 tools.
The server covers many areas (appointments, patients, financial, procedures, stock, etc.), suggesting broad functionality. However, the fragmentation obscures gaps and makes it difficult to determine if all CRUD operations exist for each entity. Some areas (e.g., stock write) have multiple tools for single actions.